AI Engineer Intern
NUST SEECS · Islamabad Aug 2026 – PresentDesign machine learning and deep learning solutions; research model architectures for scalable AI deployment.
Design machine learning and deep learning solutions; research model architectures for scalable AI deployment.
Prepared datasets, trained and tuned ML and vision models, and built API-based AI applications.
NumPy, Pandas, EDA and feature engineering.
Supervised, unsupervised and reinforcement learning.
CNN, ResNet50, YOLO11, TensorFlow, Keras and PyTorch.
Image classification and real-time emotion detection.
Embeddings, retrieval pipelines and LLM integration.
API-based applications and end-to-end AI pipelines.
The pipeline transcribes videos into text using OpenAI Whisper, splitting the data into detailed chunks. These text chunks and user queries are then converted into vectors for the RAG setup. Finally, a Large Language Model (LLM) uses the retrieved context to generate accurate answers.
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Python (NumPy, Pandas), SQL, ML, EDA, visualization, PCA, model evaluation and selection, deep learning, LLM fundamentals, generative AI and hands-on projects.
Core Python, object-oriented programming, data structures, file handling and projects.